Paper Info
Title
Extraction of Discriminative Functional MRI Activation Patterns and an Application to Alzheimer's Disease
Abstract
We propose a novel Dynamic Recursive Partitioning approach for discovering discriminative patterns of functional MRI activation. The goal is to efficiently identify spatial regions that are associated with non-spatial variables through adaptive recursive partitioning of the 3D space into a number of hyper-rectangles utilizing statistical tests. As a case study, we analyze fMRI datasets obtained from a study that explores neuroanatomical correlates of semantic processing in Alzheimer's disease. We seek to discover brain activation areas that discriminate controls from patients. We evaluate the results by presenting classification experiments that utilize information extracted from these regions. The discovered areas elucidated large hemispheric and lobar differences being consistent with prior findings. The overall classification accuracy based on activation patterns in these areas exceeded 90%. The proposed approach being general enough has great potential for elucidating structure-function relationships and can be valuable to human brain mapping.
Year
DOI
Venue
2004
10.1007/978-3-540-30136-3_89
Lecture Notes in Computer Science
Keywords
Field
DocType
spatial variability,semantic processing,information extraction,structure function,recursive partitioning,statistical test,discriminant function
Semantic memory,Disease,Pattern recognition,Computer science,Brain activation,Recursive partitioning,Human brain,Artificial intelligence,Discriminative model,Machine learning,Statistical hypothesis testing
Conference
Volume
ISSN
Citations 
3217
0302-9743
12
PageRank 
References 
Authors
1.63
4
9
Name
Order
Citations
PageRank
Despina Kontos117834.59
Vasileios Megalooikonomou256864.84
Dragoljub Pokrajac326419.89
Aleksandar Lazarevic4115756.50
Zoran Obradovic51110137.41
Orest B Boyko6121.97
James Ford722716.26
Fillia Makedon81676201.73
Saykin Andrew J963166.57